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Background: Though artificial intelligence ("AI") has been increasingly applied to patient care, many of these predictive models are retrospective and not readily available for real-time decision-making. This survey-based study aims to evaluate implementation of a new, validated mortality risk calculator (Parkland Trauma Index of Mortality, "PTIM") embedded in our electronic healthrecord ("EHR") that calculates hourly predictions of mortality with high sensitivity and specificity. Methods: This is a prospective, survey-based study performed at a level 1 trauma center. An anonymous survey was sent to surgical providers and regarding PTIM implementation. The PTIM score evaluates 23 variables including Glasgow Coma Score (GCS), vital signs, and laboratory data. Results: Of the 40 completed surveys, 35 reported using PTIM in decision-making. Prior to reviewing PTIM, providers identified perceived top 3 predictors of mortality, including GCS (22/38, 58%), age (18/35, 47%), and maximum heart rate (17/35, 45%). Most providers reported the PTIM assisted their treatment decisions (27/35, 77%) and timing of operative intervention (23/35, 66%). Many providers agreed that PTIM integrated into rounds and patient assessment (22/36, 61%) and that it improved efficiency in assessing patients' potential mortality (21/36, 58%). Conclusions: Artificial intelligence algorithms are mostly retrospective and lag in real-time prediction of mortality. To our knowledge, this is the first real-time, automated algorithm predicting mortality in trauma patients. In this small survey-based study, we found PTIM assists in decision-making, timing of intervention, and improves accuracy in assessing mortality. Next steps include evaluating the short- and long-term impact on patient outcomes. [ABSTRACT FROM AUTHOR]

Background: Insulin resistance (IR) is a potential predictor of antidepressant treatment response. Aims: We assess changes in IR after antidepressant treatment and whether these changes have any effect on treatment response. Also, to see whether changes in IR mediates relationship between C-reactive protein (CRP) and antidepressant efficacy. Methods: This is a secondary analysis of an 8-week, open-label clinical trial with 95 adults experiencing a major depressive episode. Response to vortioxetine was measured using the Montgomery–Åsberg Depression Rating Scale (MADRS). Generalized estimating equation models were utilized for this intent-to-treat analysis. Results: When adjusted for age, sex, and body mass index, there was a significant increase in IR following treatment in the overall sample (p = 0.035). This finding was detected in treatment non-responders (p = 0.019), whereas it was not observed in responders (p = 0.329). Mediation analysis revealed that change in IR during treatment was responsible for change in MADRS as well as the relationship between baseline CRP and treatment response. Conclusions: Exacerbation of IR during antidepressant treatment mediated non-response. Conversely in treatment responders IR reduced. Like previous studies, baseline CRP moderated treatment response. This relationship was also mediated by changes in IR. These findings further elucidate the role of IR in terms of antidepressant response as well as potentially explain inflammation's relationship with the latter. [ABSTRACT FROM AUTHOR]

Background: Sleep disturbances are frequently reported in patients with major depressive disorder. We aimed to investigate the effects of vortioxetine on sleep quality and association between changes in sleep and treatment response.Methods: This study is a post-hoc analysis of a clinical trial that sought to evaluate the sensitivity to cognitive change of THINC-integrated tool in patients with major depressive disorder. In total, 92 patients (aged 18 to 65) meeting Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria for moderate or severe major depressive disorder and 54 healthy controls were included. All patients received open-label vortioxetine (10-20 mg/day, flexibly dosed) for 8 weeks. Herein, the primary outcomes of interest were changes in sleep, as measured by the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Insomnia Severity Index, between weeks 0, 2, and 8. The association between changes in sleep and depressive symptom severity was secondarily assessed.Results: We observed that sleep, as indicated by scores of Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Insomnia Severity Index, was significantly poorer in patients with major depressive disorder compared to healthy controls at weeks 0, 2, and 8 (p < 0.05). Among patients with major depressive disorder, we observed significant improvements on the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Insomnia Severity Index between weeks 0 and 8 (p < 0.05). We observed a significant association between improvements on the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Insomnia Severity Index and improvement of depressive symptoms.Conclusion: Improvement of depressive symptoms in major depressive disorder patients treated with vortioxetine was associated with significant improvements in sleep. Furthermore, improvements in sleep were predictive of antidepressant response and were linearly correlated with improvement in overall depressive symptom severity. [ABSTRACT FROM AUTHOR]

Background:: Hip arthroscopy is rapidly becoming the mainstay of treatment for femoroacetabular impingement (FAI), but remains technically demanding and has its limitations. The failures of arthroscopic FAI surgery due to inaccurate and inadequate resection are reported to be increasing. Computer-assisted surgery (CAS) can theoretically improve the accuracy and precision of the osseous resections required to treat FAI. It does so by providing a preoperative assessment tool, an intraoperative tracking device, and a robotic-assisted cutting instrument. Questions/Purposes:: The purpose of this review is to discuss the evolution of CAS to address the current limitations of arthroscopic FAI surgery and propose the features required of the ideal CAS solution for FAI. Methods:: A computerized keyword search of MEDLINE was performed for studies that investigated the use of computer assistance in FAI surgery. Data was collected on preoperative assessment tools, intraoperative navigation programs, and robotic-assisted execution of FAI surgery. Results:: Sixty-one articles were identified after the keyword search. Nineteen studies met our inclusion criteria. Thirteen studies were selected to address our study questions: three studies were analyzed for preoperative planning, six for navigated osseous resection, and four for robotic-assisted execution. Conclusion:: Navigation and robotic-assisted surgery can preoperatively plan and execute osseous resection with greater accuracy compared to freehand techniques, although the clinical success and cost-effectiveness has yet to be demonstrated. The ideal CAS solution must be able to virtually plan a resection, guide the surgeon towards accurate execution of the plan, and facilitate post-resection assessment of the adequacy of resection. [ABSTRACT FROM AUTHOR]

The specialization of contemporary academia necessitates the adoption of a multidisciplinary approach to study topics that cross multiple disciplines, including the area of medical ethics. However, the nature of multidisciplinary research is limited in some regards, further requiring some researchers to use interdisciplinary and transdisciplinary approaches. The authors present as a case study a research project in bioethics that began as an interdisciplinary study and which, through the research process, moved to being a transdisciplinary study in health ethics. They outline not only this transformation but also the strengths and difficulties of transdisciplinary research in the area of ethics. [ABSTRACT FROM AUTHOR]